merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the DARE TIES merge method using NousResearch/Meta-Llama-3.1-8B as a base.
Models Merged
The following models were included in the merge:
- nbeerbower/llama3.1-gutenberg-8B
- akjindal53244/Llama-3.1-Storm-8B
- nbeerbower/llama3.1-airoboros3.2-QDT-8B
- Sao10K/Llama-3.1-8B-Stheno-v3.4
Configuration
The following YAML configuration was used to produce this model:
models:
- model: Sao10K/Llama-3.1-8B-Stheno-v3.4
parameters:
weight: 0.2
density: 0.5
- model: akjindal53244/Llama-3.1-Storm-8B
parameters:
weight: 0.5
density: 0.5
- model: nbeerbower/llama3.1-gutenberg-8B
parameters:
weight: 0.3
density: 0.5
- model: nbeerbower/llama3.1-airoboros3.2-QDT-8B
parameters:
weight: 0.2
density: 0.5
merge_method: dare_ties
base_model: NousResearch/Meta-Llama-3.1-8B
dtype: bfloat16
name: Llama-3.1-8B-Ultra-Instruct
Use Llama 3 Instruct prompt template. Use with caution, I'm not responsible for what you do with it. All credits and thanks go to the creators of the fine tunes I've merged. In my own tests and on HF Eval it performs very well for a 8B model and I can recommend it. High quality quants by Bartowski: https://huggingface.co/bartowski/Llama-3.1-8B-Ultra-Instruct-GGUF
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 28.98 |
IFEval (0-Shot) | 80.81 |
BBH (3-Shot) | 32.49 |
MATH Lvl 5 (4-Shot) | 14.95 |
GPQA (0-shot) | 5.59 |
MuSR (0-shot) | 8.61 |
MMLU-PRO (5-shot) | 31.40 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard80.810
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard32.490
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard14.950
- acc_norm on GPQA (0-shot)Open LLM Leaderboard5.590
- acc_norm on MuSR (0-shot)Open LLM Leaderboard8.610
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard31.400